A recent study has shown that a deep learning-based artificial intelligence algorithm can improve the performance of readers in detecting lung cancers on chest radiographs.
An artificial intelligence program accurately predicts the risk that lung nodules detected on screening CT will become cancerous, according to a study published in the journal Radiology.
The U.S. FDA has authorized marketing of the GI Genius, the first device that uses artificial intelligence based on machine learning to assist clinicians in detecting lesions in the colon in real time during a colonoscopy.
Aquilion Exceed LB supports fast and efficient radiation oncology workflows without compromising on patient position, image quality, or reproducibility.
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RSIP Vision’s AI-based segmentation and measurement tool detects objects of interest and their boundaries quickly and automatically, making surgical and diagnostic measurements easier and more accurate.
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RadNet’s DeepHealth subsidiary has published results of its artifiical intelligence algorithms in Nature Medicine, illustrating an ability to detect breast cancer a year or more earlier than current practice.
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Guilford, Conn.-based Hyperfine Research, Inc. announces that it has received 510(k) clearance from the U.S. FDA for its deep-learning image analysis software.
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Northwestern University researchers have developed an artificial intelligence platform, called DeepCOVID-XR, which spotted COVID-19 in x-rays faster and more accurately than thoracic radiologists in a recent study.
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